discover_music

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'smart recommendations based on your preferences and library,' which hints at personalization and data usage, but doesn't clarify how preferences are determined, what 'library' refers to (e.g., Plex library), whether this is a read-only operation, rate limits, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core functionality ('Natural language music discovery') and adds key details ('with smart recommendations based on your preferences and library'). There's no wasted verbiage, and it's appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage context, and output format. Without annotations or an output schema, the description should do more to compensate, but it falls short, leaving the agent with incomplete information for effective tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters (query, context, limit) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain how parameters interact (e.g., how 'context' modifies 'query') or provide examples beyond the schema's examples. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Natural language music discovery with smart recommendations based on your preferences and library.' It specifies the verb ('discovery'), resource ('music'), and key capabilities (natural language input, recommendations, personalization). However, it doesn't explicitly differentiate from sibling tools like 'search_plex' or 'browse_library' which might also help find music.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'search_plex' or 'browse_library' that might serve similar purposes, nor does it specify prerequisites (e.g., whether authentication or library access is needed) or exclusions (e.g., when not to use it). Usage is implied through the description but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.